Asymptotic distribution of regression correlation coefficient for Poisson regression model

Takeshi Kurosawa and Nobuhiro Suzuki

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 1, 166-180

Abstract: This study treats an asymptotic distribution for measures of predictive power for generalized linear models (GLMs). We focus on the regression correlation coefficient (RCC) that is one of the measures of predictive power. The RCC, proposed by Zheng and Agresti is a population value and a generalization of the population value for the coefficient of determination. Therefore, the RCC is easy to interpret and familiar. Recently, Takahashi and Kurosawa provided an explicit form of the RCC and proposed a new RCC estimator for a Poisson regression model. They also showed the validity of the new estimator compared with other estimators. This study discusses the new statistical properties of the RCC for the Poisson regression model. Furthermore, we show an asymptotic normality of the RCC estimator.

Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:47:y:2018:i:1:p:166-180

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DOI: 10.1080/03610926.2017.1300285

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